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LLM Engineering

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Model training, serving, retrieval, evaluation, efficiency, alignment, and infrastructure.

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Filtering this domain · category serving-and-retrieval · 19 matching cards.

CATEGORYmodels-and-training44 public cardsCATEGORYserving-and-retrieval19 public cardsCATEGORYevaluation5 public cardsCATEGORYinference-and-quantization9 public cardsCATEGORYmlops-and-ml-systems6 public cardsCATEGORYrag-and-knowledge-systems6 public cardsCATEGORYtraining-and-fine-tuning30 public cards
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A powerful local RAG (Retrieval Augmented Generation) application that lets you chat with your PDF documents using Ollama and LangChain. This project includes multiple interfaces: a modern Next.js web app, a Streamlit interface, and Jupyter notebooks for experimentation.

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DLLM RLAgent

We also introduce a diffusion-based value model that reduces variance and improves stability during optimization. Based on TraceRL, we derive a series of diffusion language models, TraDo, which achieve state-of-the-art performance on math and coding reasoning tasks.

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I've started to work on reimplementation of the library here: FastTensors Please star it if you'd like to see GGML-compatible implementation in pure Go. Please check out my related project Booster We dream of a world where fellow ML hackers are grokking REALLY BIG GPT models in their homelabs without having GPU clusters consuming a shit tons of $$$.

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⚡LLM Zoo is a project that provides data, models, and evaluation benchmark for large language models.⚡ [[Tech Report]](assets/llmzoo.pdf) technology gifted by the creator. For example, many pioneers have made great efforts to spread the use of light bulbs and vaccines to developing countries.

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LLM Twin Course: Building Your Production-Ready AI Replica Learn to architect and implement a production-ready LLM & RAG system by building your LLM Twin From data gathering to productionizing LLMs using LLMOps good practices. by Decoding AI By finishing the "LLM Twin: Building Your Production-Ready AI Replica" free course, you will learn how to design, train, and deploy a production-ready LLM twin of yourself powered by LLMs, vector DBs, and LLMOps good practices.

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中文 &nbsp | &nbsp English &nbsp 📖 中文文档 &nbsp | &nbsp 📖 English Documentation EvalScope is a one-stop LLM evaluation framework built by the ModelScope Community. Just one command to start — it supports model capability evaluation, inference performance stress testing, and result visualization.

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PowerInfer is a CPU/GPU LLM inference engine leveraging activation locality for your device. Project Kanban https://github.com/SJTU-IPADS/PowerInfer/assets/34213478/fe441a42-5fce-448b-a3e5-ea4abb43ba23 PowerInfer v.s.

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Run Stable Diffusion on Apple Silicon with Core ML [\[Blog Post\]](https://machinelearning.apple.com/research/stable-diffusion-coreml-apple-silicon) [\[BibTeX\]](#bibtex) This repository comprises: If you run into issues during installation or runtime, please refer to the FAQ section. Please refer to the System Requirements section before getting started.

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